This application claims the priority of Korean Patent Application No. 2003-95522, filed on Dec. 23, 2003, in the Korean Intellectual Property Office, the disclosure of which is incorporated herein in its entirety by reference.
1. Field of the Invention
The present invention relates to a mobile device, and more particularly, to a method and apparatus for obtaining an amount of rotational movement of a mobile device and using the same, and a computer-readable recording medium for storing a computer program.
2. Description of the Related Art
In general, in order to automatically control a moving object (hereinafter referred to as mobile device), the posture of the mobile device should be obtained in real time. Posture means information on the position and pose of the mobile device. A conventional method in which the mobile device itself obtains the posture is largely classified into one of: a local tracking method and a global localization method. These methods are disclosed for instance on page 10 of a technical report entitled “Where am I? Sensors and Methods for Mobile Robot Positioning” written by J. Borenstein, H. R. Everett, and L. Feng, published on April 1996 and prepared by the University of Michigan for the Oak Ridge National Laboratories D & D Program.
According to the local tracking method of the disclosed methods, the posture can be simply recognized using an odometry. However, this method has a problem of being sensitive to a kinematic modeling error and a unstructured error. To solve the problem, a variety of types of error modeling and compensation methods have been developed and are disclosed for example on pages 132-150 of the above technical report, a thesis entitled “Measurement and Correction of Systematic Odometry Errors in Mobile Robots” (J. Borenstein, and L. Feng, IEEE Transactions on Robotics and Automation, Vol. 12, No. 6, December 1996, pp. 869-880), and a thesis entitled “Relative Localization using Path Odometry Information” (Nakju Lett Doh, Howie Choset, and Wan Kyun Chung, submitted to IEEE Transactions on Robotics and Automation). These error modeling and compensation methods are limited to being applied only when the structured errors can be mathematically expressed.
Thus, the position of the mobile device is estimated using a linear accelerometer while the pose of the mobile device is estimated using a gyro or compass. In this case, conventional filter design methods to stably estimate the posture from a sensed signal exist. However, the conventional method of estimating the posture by integrating the sensed result has problems of not only considerably degrading accuracy in recognizing posture as time passes due to accumulated integral errors, and but also using expensive sensors.
To solve the above problems, there is a conventional method of estimating a relative movement of a mobile device using flow of a camera image every hour by utilizing a vision system. However, although this method is processed by a simple system structure, a calculation time to process the image flow is prolonged.